Retinal image quality assessment (IQA) is a step in screening systems for diseases like diabetic retinopathy (DR), glaucoma and age related macular degeneration (AMD) which require rapid and accurate evaluation. For example, color funds retinal image assessment is used to diagnose such diseases. Digital fundus photography of the retina is an effective non-invasive examination medium of many retinal conditions with the potential to reduce workload of ophthalmologists and increase the cost effectiveness of screening systems. Medical image quality assessment has not be much explored since many studies report a significant percentage of acquired study images to be of insufficient quality for an automated assessment. Poor quality images have to be discarded. Existing approaches to IQA use hand crafted features which are not inclusive and do not generalize well to new datasets. Neither do they leverage the functioning of the human visual system (HVS) to improve IQA algorithms.